Resumen

LEAL NARVAEZ, ESMEIDE A; BRANCH, JOHN WILLIAM  y  ORTEGA LOBO, OSCAR. ESTIMATION OF CURVATURES AND PRINCIPALS DIRECTIONS IN UNORGANIZED POINTS CLOUD. Dyna rev.fac.nac.minas [online]. 2007, vol.74, n.153, pp.351-362. ISSN 0012-7353.

The computation of principal curvatures and directions is important in different fields like computer vision, pattern recognition and 3D object reconstruction. Curvatures and directions are properties that must be estimated in discrete form, since the rendering primitives are data points that have neither interconnection nor orientation. This paper present a method to estimate principal curvatures and directions from an unorganized-points cloud sampled from 3D surfaces. The proposed method does not require estimation of intermediates global structures like triangular mesh or local approximation. Instead, the method estimates the local geodesic neighborhood around each point in the cloud. Numerical and graphical validations are presented, showing the efficacy of the method.

Palabras clave : Principal curvatures and directions estimation; Normal estimation; noise; geodesic neighborhood; PCA.

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